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In this chapter, the coal market analysis was conducted in selected countries, such as China, the United States, and Poland. The availability of coal resources throughout the world and the structure of energy production systems selected for the analysis of countries were characterized. Machine learning algorithms, the Boltzmann, Gompretz, Holt-Winters models, and the random forest algorithm were used in creation of CFP 1.0 programme. It allowed to determine forecasts of the demand for energy from coal, CO2 emissions, and coal prices on international markets. Factors from the SGD7 set that will have the greatest impact on the development of CCT were also identified. Alternative energy sources were indicated that could theoretically take over the role of coal in the near future.

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Coal Market

  • 章节

  • 发表日期：

    2025年

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  • Aurelia Rybak,
  • Aleksandra Rybak

摘要

In this chapter, the coal market analysis was conducted in selected countries, such as China, the United States, and Poland. The availability of coal resources throughout the world and the structure of energy production systems selected for the analysis of countries were characterized. Machine learning algorithms, the Boltzmann, Gompretz, Holt-Winters models, and the random forest algorithm were used in creation of CFP 1.0 programme. It allowed to determine forecasts of the demand for energy from coal, CO2 emissions, and coal prices on international markets. Factors from the SGD7 set that will have the greatest impact on the development of CCT were also identified. Alternative energy sources were indicated that could theoretically take over the role of coal in the near future.